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3D Point Cloud Classification

11 papers with code · Computer Vision

Image: Qi et al

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Greatest papers with code

Dynamic Graph CNN for Learning on Point Clouds

24 Jan 2018WangYueFt/dgcnn

Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices.

3D POINT CLOUD CLASSIFICATION SEMANTIC SEGMENTATION

Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

12 Apr 2017nsavinov/semantic3dnet

With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks.

3D POINT CLOUD CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION

Geometry Sharing Network for 3D Point Cloud Classification and Segmentation

23 Dec 2019MingyeXu/GS-Net

Specially, GS-Net consists of Geometry Similarity Connection (GSC) modules which exploit Eigen-Graph to group distant points with similar and relevant geometric information, and aggregate features from nearest neighbors in both Euclidean space and Eigenvalue space.

3D POINT CLOUD CLASSIFICATION

Adversarial point perturbations on 3D objects

16 Aug 2019Daniel-Liu-c0deb0t/Adversarial-point-perturbations-on-3D-objects

The importance of training robust neural network grows as 3D data is increasingly utilized in deep learning for vision tasks, like autonomous driving.

3D POINT CLOUD CLASSIFICATION AUTONOMOUS DRIVING

Transductive Zero-Shot Learning for 3D Point Cloud Classification

16 Dec 2019ali-chr/Transductive_ZSL_3D_Point_Cloud

This paper extends, for the first time, transductive Zero-Shot Learning (ZSL) and Generalized Zero-Shot Learning (GZSL) approaches to the domain of 3D point cloud classification.

3D POINT CLOUD CLASSIFICATION IMAGE CLASSIFICATION ZERO-SHOT LEARNING

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

9 Feb 2020minzhang-1/PointHop2

The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.

3D POINT CLOUD CLASSIFICATION

Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification

14 Oct 2019lixiang-ucas/DANCE-NET

Based on this convolution module, we further developed a multi-scale fully convolutional neural network with downsampling and upsampling blocks to enable hierarchical point feature learning.

3D POINT CLOUD CLASSIFICATION